Gen AI - Senior Associate

A career within our Infrastructure practice will provide you with the opportunity to design, build, coordinate and maintain the IT environments for clients to run internal operations, collect data, monitor, develop and launch products. Infrastructure management consists of hardware, storage, compute, network and software layers.

As a part of our Infrastructure Engineering team, you will be responsible for maintaining the critical IT systems which includes build, run and maintenance while providing technical support and training that aligns to industry leading practices.

• Use feedback and reflection to develop self awareness, personal strengths and address development areas.
• Delegate to others to provide stretch opportunities, coaching them to deliver results.
• Demonstrate critical thinking and the ability to bring order to unstructured problems.
• Use a broad range of tools and techniques to extract insights from current industry or sector trends.
• Review your work and that of others for quality, accuracy and relevance.
• Know how and when to use tools available for a given situation and can explain the reasons for this choice.
• Seek and embrace opportunities which give exposure to different situations, environments and perspectives.
• Use straightforward communication, in a structured way, when influencing and connecting with others.
• Able to read situations and modify behavior to build quality relationships.
• Uphold the firms code of ethics and business conduct.

• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field with a focus on generative models
• 3+ years of hands-on experience developing and deploying AI models in production environments with 1 year of experience in developing generative AI pilots, proofs of concept, and prototypes
• Deep understanding of state-of-the-art AI architectures (e.g., Transformers, VAEs, GANs, Diffusion Models)
• Expertise in PyTorch or TensorFlow, with a preference for experience in both
• Proficiency in Python and software engineering best practices for AI systems

• Required
  • Demonstrated experience with large language models (LLMs) such as GPT, BERT, T5, etc.
  • Practical understanding of generative AI frameworks (e.g., Hugging Face Transformers, OpenAI GPT, DALL-E)
  • Familiarity with prompt engineering and few-shot learning techniques
  • Expertise in MLOps and LLMOps practices, including CI/CD for ML models
  • Strong knowledge of one or more cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI)
• Preferred
  • Proficiency in optimizing generative models for inference (quantization, pruning, distillation)
  • Experience with distributed training of large-scale AI models
  • Experience with model serving technologies (e.g., TorchServe, TensorFlow Serving, Triton Inference Server)

• Architect and implement end-to-end generative AI solutions, from data preparation to production deployment
• Develop custom AI models and fine-tune pre-trained models for specific client use cases
• Optimize generative models for production, balancing performance, latency, and resource utilization
• Design and implement efficient data pipelines for training and serving generative models
• Develop strategies for effective prompt engineering and few-shot learning in production systems
• Implement robust evaluation frameworks for generative AI outputs
• Collaborate with cross-functional teams to integrate generative AI capabilities into existing systems
• Address challenges related to bias, fairness, and ethical considerations in generative AI applications

• Lead the technical aspects of generative AI projects from pilot to production
• Develop proof-of-concepts and prototypes to demonstrate the potential of generative AI in solving client problems
• Conduct technical feasibility studies for applying generative AI to novel use cases
• Implement monitoring and observability solutions for deployed generative models
• Troubleshoot and optimize generative AI systems in production environments

• Provide expert technical guidance on generative AI capabilities and limitations to clients
• Collaborate with solution architects to design generative AI-powered solutions that meet client needs
• Present technical approaches and results to both technical and non-technical stakeholders
• Assist in scoping and estimating generative AI projects

• Stay at the forefront of generative AI research and industry trends
• Contribute to the companys intellectual property through patents or research publications
• Develop internal tools and frameworks to accelerate generative AI development
• Mentor junior team members on generative AI technologies and best practices
• Contribute to technical blog posts and whitepapers on generative AI applications

Degrees/Field of Study required: Degrees/Field of Study preferred: